Reflective Intelligence Augmentation

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Revision as of 23:07, 1 December 2023 by Navis (talk | contribs) (Created page with "== Thought == Internal dialogue about the potential of combining human reflective thinking with artificial intelligence to augment and scale our cognitive processes. == Note == Reflective intelligence augmentation combines AI with human reasoning to enhance cognitive abilities. == Analysis == Reflective thinking involves a deep analysis of ideas or situations, often to understand and improve upon them. We know that AI has strength in processing vast amounts of data and...")
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Thought

Internal dialogue about the potential of combining human reflective thinking with artificial intelligence to augment and scale our cognitive processes.

Note

Reflective intelligence augmentation combines AI with human reasoning to enhance cognitive abilities.

Analysis

Reflective thinking involves a deep analysis of ideas or situations, often to understand and improve upon them. We know that AI has strength in processing vast amounts of data and recognizing patterns. By integrating AI into our reflective thoughts, we can create a collaborative system where AI aids in the first-level processing of data, which is then subject to human reflective thought for context, ethics, cultural understanding, and creativity.

How might such a system fit into Koestler's idea of bisociation? Koestler's concept refers to creative thinking that connects unrelated matrices of thought. Here, AI and human cognition are ostensibly different systems of processing, but their association in a structured way could lead to creative leaps that neither could achieve independently.

Books

  • "The Society of Mind" by Marvin Minsky – discusses the mind as a collection of agents.
  • "The Master Algorithm" by Pedro Domingos – outlines how algorithms could be the key to unifying the fields of artificial intelligence.
  • "Thinking, Fast and Slow" by Daniel Kahneman – differentiates between two systems of thought: one fast and intuitive, the other slow and deliberate.

Papers

  • "Reflection and Reasoning in Moral Judgment" by Joshua D. Greene – provides insight into the dual-process theories of moral reasoning.
  • "Reward is enough" by Silver et al. – discusses how reward-based learning could be the key to AI development.